Tags: Geographic Information System (GIS)

Teaching Materials (1-9 of 9)

  1. Assessing Socioeconomic Trends in Tree Cover and Human Health in Urban Environments

    02 Aug 2021 | Teaching Materials | Contributor(s):

    By Tamara Basham

    Collin County Commuity College District

    In this exercise, students use a combination of publicly available data and tree cover data that they generate using iTree Canopy to test whether tree cover is equitably distributed within the city...

    https://qubeshub.org/publications/2363/?v=1

  2. Earth Analytics Bootcamp Course

    15 Oct 2019 | Teaching Materials | Contributor(s):

    By Jenny Palomino1, Leah Wasser

    Earth Lab - University of Colorado, Boulder

    The Earth Analytics Bootcamp is a three-week introductory-level course taught by instructors in Earth Lab and is a part of the Professional Certificate in Earth Data Analytics - Foundations at CU...

    https://qubeshub.org/publications/1438/?v=1

  3. Earth Analytics in Python Course

    01 Nov 2019 | Teaching Materials | Contributor(s):

    By Leah Wasser1, Jenny Palomino1, Chris Holdgraf2

    1. Earth Lab - University of Colorado, Boulder 2. University of California, Berkeley

    Earth analytics is an intermediate, multidisciplinary course that addresses major questions in Earth science and teaches students to use the analytical tools necessary to undertake exploration of...

    https://qubeshub.org/publications/1437/?v=1

  4. Earth Analytics in R Course

    15 Oct 2019 | Teaching Materials | Contributor(s):

    By Leah Wasser

    Earth Lab - University of Colorado, Boulder

    Earth analytics is an advanced, multidisciplinary course that addresses major questions in Earth science and teaches students to use the analytical tools necessary to undertake exploration of...

    https://qubeshub.org/publications/1439/?v=1

  5. Get Started With GIS in Open Source Python Workshop

    15 Oct 2019 | Teaching Materials | Contributor(s):

    By Leah Wasser1, Jenny Palomino1, Joe McGlinchy1

    Earth Lab - University of Colorado, Boulder

    There are a suite of powerful open source python libraries that can be used to work with spatial data. Learn how to use geopandas, rasterio and matplotlib to plot and manipulate spatial data in...

    https://qubeshub.org/publications/1441/?v=1

  6. Introduction to Earth Data Science Textbook

    15 Oct 2019 | Teaching Materials | Contributor(s):

    By Jenny Palomino, Leah Wasser

    Introduction to Earth Data Science is an online textbook for anyone new to open reproducible science and the Python programming language. There are no prerequisites for this material, and no prior...

    https://qubeshub.org/publications/1440/?v=1

  7. Investigating Sexually Transmitted Disease (STD) Ecologies Using Geographic Information Systems (GIS) (Abstract) | TIEE

    12 Jun 2018 | Teaching Materials | Contributor(s):

    By Maruthi Bhaskar

    Texas Southern University

    Identifying, mapping and understanding the magnitude and the spatial prevalence of the Sexually Transmitted Diseases (STDs) such as chlamydia and gonorrhea diseases. Analyzing the spatial trends of...

    https://qubeshub.org/publications/423/?v=1

  8. Island biogeography, spatial ecology, and macroinvertebrate species diversity in Richmond’s rock pools

    22 Feb 2019 | Teaching Materials | Contributor(s):

    By Nadia Bukach1, Todd Lookingbill1, Andrew Davidson2, James R Vonesh2, Kristine Grayson1

    1. University of Richmond 2. Virginia Commonwealth University

    Students investigate questions of community ecology and biogeography using data from an urban rock pool ecosystem. Using ArcGIS 10, students learn to create effective maps, calculate landscape...

    https://qubeshub.org/publications/1056/?v=1

  9. Writing Clean Code in R Workshop

    15 Oct 2019 | Teaching Materials | Contributor(s):

    By Max Joseph1, Leah Wasser

    Earth Lab - University of Colorado, Boulder

    When working with data, you often spend the most amount of time cleaning your data. Learn how to write more efficient code using the tidyverse in R.

    https://qubeshub.org/publications/1442/?v=1